I. Field
The present disclosure relates generally to communication, and more specifically to techniques for computing log-likelihood ratio (LLRs) for code bits.
II. Background
In a communication system, a transmitter typically encodes traffic data based on a coding scheme to obtain code bits and further maps the code bits to modulation symbols based on a modulation scheme. The transmitter then processes the modulation symbols to generate a modulated signal and transmits this signal via a communication channel. The communication channel distorts the transmitted signal with a channel response and further degrades the signal with noise and interference.
A receiver receives the transmitted signal and processes the received signal to obtain received symbols, which may be distorted and noisy versions of the modulation symbols sent by the transmitter. The receiver may then compute LLRs for the code bits based on the received symbols. The LLRs are indicative of the confidence in zero (‘0’) or one (‘1’) being sent for each code bit. For a given code bit, a positive LLR value may indicate more confidence in ‘0’ being sent for the code bit, a negative LLR value may indicate more confidence in ‘1’ being sent for the code bit, and an LLR value of zero may indicate equal likelihood of ‘0’ or ‘1’ being sent for the code bit. The receiver may then decode the LLRs to obtain decoded data, which is an estimate of the traffic data sent by the transmitter.
The computation for the LLRs may be complex. However, accurate LLRs may result in good decoding performance. There is therefore a need in the art for techniques to efficiently and accurately compute LLRs for code bits.